Maintenance and Crew Considerations in Fleet Assignment

Belobaba

Odoni

2003

Transportation Science

227

121

T his paper presents an overview of several important areas of operations research applications in the air transport industry. Specific areas covered are: the various stages of aircraft and crew schedule planning; revenue management, including overbooking and legbased and network-based seat inventory management; and the planning and operations of aviation infrastructure (airports and air traffic management). For each of these areas, the paper provides a historical perspective on OR contributions, as well as a brief summary of the state of the art. It also identifies some of the main challenges for future research.

Section: Aircraft Maintenance Routingmentioning

confidence: 99%

Applications of Operations Research in the Air Transport Industry

Belobaba

Odoni

2003

Transportation Science

227

121

“…Nonetheless, airline schedule planners have keen interest in improving upon the sequential solution approach, with its costly impact on crew scheduling. Clarke et al (1996a) and Barnhart et al (1998a) have taken steps towards integrating fleet assignment and crew scheduling by modifying fleet assignment models to account for some of the downstream effects on crews. Clarke et al (1996a) include bonuses for fleet assignments that allow crews to stay with the same aircraft.…”

Section: Integrating Core Modelsmentioning

confidence: 99%

“…Clarke et al (1996a) and Barnhart et al (1998a) have taken steps towards integrating fleet assignment and crew scheduling by modifying fleet assignment models to account for some of the downstream effects on crews. Clarke et al (1996a) include bonuses for fleet assignments that allow crews to stay with the same aircraft. This reduces the occurrence of extended periods of crew rest between flights (the fleet assignment objective indirectly works to achieve solutions with high aircraft utilization), thereby eliminating unnecessary crew inactivity and costs.…”

Section: Integrating Core Modelsmentioning

confidence: 99%

Airline Schedule Planning: Accomplishments and Opportunities

Cohn

2004

M&SOM

P lagued by high labor costs, low profitability margins, airspace and airport congestion, high capital and operating costs, security and safety concerns, and complex and large-scale management and operations decisions, the airline industry has armed its planners with sophisticated optimization tools to improve decision making and increase airline profits. In this paper, we describe optimization approaches for airline schedule planning, demonstrating how optimization can facilitate the management of a diverse and finite set of expensive, highly constrained resources. We focus on the art and science of modeling and solving these problems, providing illustrative examples of the associated impacts and challenges, and highlighting effective techniques that might be applicable to problems arising in other industries.

“…Hane et al [10] use a similar multicommoditv network flow formulation to solve the basic fleet assignment problem, but their use of variable aggregation, cost perturbations, dual simplex with steepest-edge pricing, and intelligent branch-and-bound strategies result in a rapid solution to realistically-sized (2500-flight, eleven-fleet) problems. Gu et al [9] study the complexity and behavior of the model presented in the Hane paper, while in Clarke et al [4], a sequel to the Hane paper, it is shown that better operational solutions to the fleet assignment problem can be achieved by adding variables and constraints that model maintenance and crew issues.…”

Section: Literature Reviewmentioning

confidence: 99%

Airline Fleet Assignment with Time Windows

Rexing

Kniker

et al. 2000

Transportation Science

127

Current fleet assignment models allow no variability in the scheduled departure time of flights even though exploiting this variability can result in more flight connection opportunities and a more cost effective fleet assignment. We present a generalized model that exploits this variability, simultaneously assigning aircraft types to flights and scheduling flight departures.We model this problem as a simple variant to current fleet assignment models, assigning a time window to each flight and then discretizing each window, allowing the model to select the departure time. As problem size can become formidable, much larger than current fleet assignment models, we develop two algorithmic approaches for solving the model. Our direct solution approach is good for speed and simplicity, while our iterative technique minimizes memory usage.Using data from a major U.S. airline. we show that our model can solve real, large-scale problems, and we evaluate the effects of schedule flexibility. In every test scenario, the model produces a fleet assignment with significantly lower costs than the basic model, and in a separate analysis, the model is used to tighten the schedule, potentially saving aircraft.